Data Engineer - Marham

About the job

• Build and maintain data pipelines using Python and Apache Spark.
• Orchestrate workflows using Airflow and Google Cloud Workflows (CloudFlow).
• Develop, deploy, and manage containerized data services using Docker and Cloud Run.
• Design, optimize, and monitor datasets and queries in BigQuery.
• Ingest, transform, and integrate external data through REST APIs.
• Manage data lifecycle and storage using Google Cloud Storage (GCS).
• Implement data quality, monitoring, and observability best practices.
• Collaborate with cross-functional engineering, product, and data science teams.

Requirements

• 2–4+ years of experience as a Data Engineer or similar role.
  
• Strong proficiency in Python, SQL, and Spark/PySpark.
  
• Hands-on experience with Airflow and cloud-native orchestration (e.g., Cloud Workflows).
  
• Experience with Docker, containers, and deploying services in Cloud Run.
  
• Skilled with BigQuery, GCS, and general GCP data tooling.
  
• Experience working with REST APIs and building ingestion integrations.
  
• Solid understanding of data modeling, ETL/ELT pipelines, and distributed systems.

Bonus: Experience with healthcare data standards (FHIR, HL7) or regulated environments.

Benefits

• Competitive salary and performance-based incentives
• Flexible work arrangements
• Paid time off and public holidays
• Professional development opportunities (training, workshops, certifications)
• Supportive, collaborative, and mission-driven work culture